MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL

Guan Jie Hua, Che Lun Hung*, Chun Yuan Lin, Fu Che Wu, Yu Wei Chan, Chuan Yi Tang

*此作品的通信作者

研究成果: Review article同行評審

12 引文 斯高帕斯(Scopus)

摘要

A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phylogenetic tree by calculating pairwise genetic distances between taxa. These methods have the computational performance issue. Although several new methods with high-performance hardware and frameworks have been proposed, the issue still exists. In this work, a novel parallel Unweighted Pair Group Method with Arithmetic Mean approach on multiple Graphics Processing Units is proposed to construct a phylogenetic tree from extremely large set of sequences. The experimental results present that the proposed approach on a DGX-1 server with 8 NVIDIA P100 graphic cards achieves approximately 3-fold to 7-fold speedup over the implementation of Unweighted Pair Group Method with Arithmetic Mean on a modern CPU and a single GPU, respectively.

原文English
期刊Evolutionary Bioinformatics
13
DOIs
出版狀態Published - 3 10月 2017

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